Health care is one of the key essential services to be traditionally impacted by financial turbulences. The Government of India announced the demonetization of INR 500 and INR 1000 currency notes in November 2016 to curb corruption and introduce economic transparency. The present commentary analyzes the impact of this economic reform on the availability/delivery of health-care services and also its transient effect on the general population availing such services during the first 2 weeks post demonetization. While print and electronic media indicated initial setback and displeasure with reference to delivery and access of health-care services, personal interaction with caregivers or patients suggested that there was no lasting adverse effect on health-care delivery. In fact, the enthusiasm for a cleaner economy meant for the greater good of the country prevailed among the general public and allowed them to bear these hardships. Our assessment suggests that demonetization and its consequential transition were viewed favorably. Financial and economic reforms initiated in the national interest can therefore be managed well with public support.
Background: Accidental Injury is a traumatic event which not only influences physical, psychological, and social wellbeing of the households but also exerts extensive financial burden on them. Despite the devastating economic burden of injuries, in India, there is limited data available on injury epidemiology. This paper aims to, first, examine the socio-economic differentials in Out of Pocket Expenditure (OOPE) on accidental injury; second, to look into the level of Catastrophic Health Expenditure (CHE) at different threshold levels; and last, to explore the adjusted effect of various socio-economic covariates on the level of CHE. Methods: Data was extracted from the key indicators of social consumption in India: Health, National Sample Survey Organisation (NSSO), conducted by the Government of India during January-June-2014. Logistic regression analysis was employed to analyse the various covariates of OOPE and CHE associated to accidental injury. Findings: Binary Logistic analysis has demonstrated a significant association between socioeconomic status of the households and the level of OOPE and CHE on accidental injury care. People who used private health services incurred 16 times higher odds of CHE than those who availed public facilities. The result shows that if the person is covered via any type of insurance, the odd of CHE was lower by about 28% than the uninsured. Longer duration of stay and death due to accidental injury was positively associated with higher level of OOPE. Economic status, nature of healthcare facility availed and regional affiliation significantly influence the level of OOPE and CHE. Conclusion: Despite numerous efforts by the Central and State governments to reduce the financial burden of healthcare, large number of households are still paying a significant amount from their own pockets. There are huge differentials in cost for the treatment among public and private healthcare providers for accidental injury. It is expected that the findings would provide insights into the prevailing magnitude of accidental injuries in India, the profile of the population affected, and the level of OOPE among households.
Over the years extreme weather events have been catastrophic and continue to have overwhelming impacts globally, mainly due to climate change. However, the impacts of extreme weather events have been uneven and devastating in developing countries largely because of lack of resources, weak adaptive capacity and large dependency on climate sensitive livelihoods. Odisha on the eastern coast of India is one of the most disaster-prone states in India with a regular prevalence of extreme events like cyclones, droughts, floods and heat waves. The state's livelihood is mainly based on weather patterns directly (farming, fisheries) or indirectly (non-farm wage labour, dairy farming) are at stake due to the frequent occurrence of extreme weather events. However, there are very limited studies available which describe the situation, impacts and resilience of extreme weather events in the context of livelihood in the state. The present study is an attempt in this direction to review and examine the impact of extreme weather events (e.g., cyclone, flood, drought and heat wave) on the livelihood of the population in Odisha. In addition, the study examines the resilience shown by the people and the program and policy adopted by the government on the extreme weather events in the state. The study findings highlight that extreme weather events have affected populations at large, caused substantial economic losses and exerted a disproportionate effect on the vulnerable social groups such as sharecroppers, small and marginal farmers, backward communities, landless labourers, wage labourers, rickshaw pullers and vendors as the nature of work in which they are engaged is susceptible to the effects of extreme weather events. Heat waves, droughts, floods and cyclones are the important extreme weather events that hamper the livelihoods in Odisha. Frequent occurrence of events has caused a blow to the livelihood resilience of the poor and marginalized people. While immediate coping mechanisms at the local level do provide some relief to ...
BACKGROUND: Gestational diabetes mellitus (GDM) causes several maternal and neonatal complications. AIMS: This exploratory study was conducted to estimate the prevalence, determine the risk factors and morbidities among pregnant women. METHODS: In this prospective study, 1557 pregnant women attending the Gyn. & Obs. clinic of a hospital in an urban area of Bhubaneswar were enrolled. Various socio-demographic factors and clinical profiles were assessed. We used a Glucometer for the diagnosis of GDM. RESULTS: More younger pregnant women residing in slums, sedentary and overweight were having diabetes. A large percentage of pregnant women living in rural areas and slums visit the government hospitals as they are benefitted by the State govt.'s scheme, Mamata. Pregnant women residing in the urban areas prefer to go for ante-natal check-ups in private Nursing homes/Clinics owing to the crowd and prolonged waiting hours. In this study, body mass index (BMI) and family history of the pregnant women appeared to be the significant risk factors for the gestational diabetes. Out of 1557 pregnant women, 154 were having diabetes, the prevalence being 9.89%. This is low when compared to the studies reported from other regions of the country. CONCLUSIONS: Gluco-One is suitable for screening gestational diabetes using the optimal threshold capillary glucose level of 140 mg/dl. As the pregnant women find it difficult to come the next day just to collect the results, this facilitated in getting the test results promptly and appropriate consultation by Doctor the same day. Glucometer can be used for accurate screening of gestational diabetes mellitus. Pregnant women with screening values not normal were identified on the spot and followed up at regular intervals. Screening for diabetes among pregnant women would result in early case detection indirectly resulting in better outcomes of treatment and prevention of complications.
Background An effective health workforce is essential for achieving health-related new Sustainable Development Goals. Odisha, one of the states in India with low health indicators, faces challenges in recruiting and retaining health staff in the public sector, especially doctors. Recruitment, deployment and career progression play an important role in attracting and retaining doctors. We examined the policies on recruitment, deployment and promotion for doctors in the state and how these policies were perceived to be implemented. Methods We undertook document review and four key informant interviews with senior state-level officials to delineate the policies for recruitment, deployment and promotion. We conducted 90 in-depth interviews, 86 with doctors from six districts and four at the state level to explore the perceptions of doctors about these policies. Results Despite the efforts by the Government of Odisha through regular recruitments, a quarter of the posts of doctors was vacant across all institutional levels in the state. The majority of doctors interviewed were unaware of existing government rules for placement, transfer and promotion. In addition, there were no explicit rules followed in placement and transfer. More than half (57%) of the doctors interviewed from well-accessible areas had never worked in the identified hard-to-reach areas in spite of having regulatory and incentive mechanisms. The average length of service before the first promotion was 26 (±3.5) years. The doctors expressed satisfaction with the recruitment process. They stated concerns over delayed first promotion, non-transparent deployment policies and ineffective incentive system. Almost all doctors suggested having time-bound and transparent policies. Conclusions Adequate and appropriate deployment of doctors is a challenge for the government as it has to align the individual aspirations of employees with organizational needs. Explicit rules for human resource management coupled with transparency in implementation can improve governance and build trust among doctors which would encourage them to work in the public sector.
BACKGROUND: Since the novel SARS-CoV-2 has been detected and the ensuing pandemic, the search for a cure or prevention has been the only target of the medical fraternity. As the second wave racked havoc, vaccines seemed to be the only viable option to stop this global surge. World Health Organization (WHO) and subsequently the Government of India have issued emergency use authorization to two vaccines. Our study aims to estimate the prevalence of the anti-SARS-CoV-2 antibodies and identify predictors of antibody titers in vaccinated healthcare workers in VIMSAR, Burla. METHODS: This is a part of the ongoing, repeated cross-sectional study. Participants were enrolled well above the sample size (322) to increase precision. Two rounds of the survey were conducted and are being reported. Serum IgG antibodies against spike protein of SARS-CoV-2 were estimated using Elecsys(®) anti-SARS-CoV-2S is an immunoassay by ECLIA-based Cobas e411 analyzer. Univariate and multivariate regression were used in statistical analysis. RESULTS: Our results show that 95.1% and 99.5% of the vaccinated individuals have developed antispike protein antibodies after the first and second doses, respectively. Previous COVID-19 infection was significantly correlated with antibody production, and age was negatively correlated. No difference was reported for sex, occupation, and diabetes. CONCLUSION: Our interim analysis report is coherent with the available literature and research regarding the high efficacy of the COVID-19 vaccine as far as seroconversion is concerned.
Background India has made substantial progress in improving child survival over the past few decades, but a comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality. Methods We assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in 5 × 5 km grids across India, and for the districts and states of India, using all accessible data from various sources including surveys with subnational geographical information. The 31 states and groups of union territories were categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from 2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and 25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We assessed the causes of child death and the contribution of risk factors to child deaths at the state level. Findings U5MR in India decreased from 83·1 (95% uncertainty interval [UI] 76·7–90·1) in 2000 to 42·4 (36·5–50·0) per 1000 livebirths in 2017, and NMR from 38·0 (34·2–41·6) to 23·5 (20·1–27·8) per 1000 livebirths. U5MR varied 5·7 times between the states of India and 10·5 times between the 723 districts of India in 2017, whereas NMR varied 4·5 times and 8·0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per 1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of change from 2010 to 2017 varied among the districts from a 9·02% (95% UI 6·30–11·63) reduction to no significant change for U5MR and from an 8·05% (95% UI 5·34–10·74) reduction to no significant change for NMR. Inequality between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to 2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate decline for neonatal disorders, and the smallest decline for congenital birth defects, although the magnitude of decline varied widely between the states. Child and maternal malnutrition was the predominant risk factor, to which 68·2% (65·8–70·7) of under-5 deaths and 83·0% (80·6–85·0) of neonatal deaths in India could be attributed in 2017; 10·8% (9·1–12·4) of under-5 deaths could be attributed to unsafe water and sanitation and 8·8% (7·0–10·3) to air pollution. Interpretation India has made gains in child survival, but there are substantial variations between the states in the magnitude and rate of decline in mortality, and even higher variations between the districts of India. Inequality between districts within states has increased for the majority of the states. The district-level trends presented here can provide crucial guidance for targeted efforts needed in India to reduce child mortality to meet the Indian and global child survival targets. District-level mortality trends along with state-level trends in causes of under-5 and neonatal death and the risk factors in this Article provide a comprehensive reference for further planning of child mortality reduction in India.
Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations. ; Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi's work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge's work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia's research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities. ; Peer reviewed